The use of videoconferencing is ever expanding, particularly in light of the trend for corporate employees to be working at a mobile work location away from a traditional office, and the increasing speed and affordability of sufficiently fast cameras, networks, computer systems, etc. However, when an employee is located in a non-traditional work location, such as a home office, vacation location, etc., the background of the video feed for the employee can become distracting to other videoconference participants and/or project an undesirable image to a current or prospective customer of the employer.
A current approach to address these issues is to selectively locate the video conference camera and/or configure the background so that the background is innocuous. For example, the person can sit in front of a blank wall, a hanging sheet, and/or the like. Another approach uses image processing to blur portions of the image that correspond to the background.
In various applications, such as news reporting, image data corresponding to the individual is isolated from background image data, which is replaced with image data for another background. Various approaches can identify and separate an individual's face and/or torso from a background without requiring a fixed background of a unique color (e.g., a green screen). For example, an approach uses generic shape-based probabilistic spatio-temporal video object segmentation to isolate an individual from the actual background and merge the individual with a desired background.